Study on Grade Prediction of Flotation Concentrate Based on Modified Artificial Fish Swarm Algorithm

DOI

10.2991/msbda-19.2019.24How to use a DOI?

Keywords

Artificial fish swarm algorithm, Flotation, Support vector machine

Abstract

Flotation is a process with nonlinear, large lag, strong coupling and other characteristics, concentrate grade is an important economic index to test the flotation production process, and it is difficult to establish accurate mathematical model, accurate prediction of concentrate grade is needed, which is of great significance to the quality prediction of flotation process.Support vector machine regression prediction was used as basic model, and modified basic artificial fish swarm algorithm(AFSA) was used to optimize parameters about the model, and GAFSA-SVM model was established to predict flotation concentrate grade.The initial value, crowding factor and visual field of the AFSA are improved, and the elimination mechanism is added.By simulating the historical data, the improved gafsa-svm model can predict the flotation concentrate grade well, effectively improve the prediction accuracy and speed of concentrate grade, and meet the requirements of field practice.

Copyright

© 2019, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Yong Zhang
AU  - Hongyang Ren
AU  - Zhongfeng Li
PY  - 2019/08
DA  - 2019/08
TI  - Study on Grade Prediction of Flotation Concentrate Based on Modified Artificial Fish Swarm Algorithm
BT  - Proceedings of the 2019 International Conference on Modeling, Simulation and Big Data Analysis (MSBDA 2019)
PB  - Atlantis Press
SP  - 154
EP  - 159
SN  - 2352-538X
UR  - https://doi.org/10.2991/msbda-19.2019.24
DO  - 10.2991/msbda-19.2019.24
ID  - Zhang2019/08
ER  -